{"id":18946,"date":"2025-02-25T19:52:18","date_gmt":"2025-02-25T19:52:18","guid":{"rendered":"https:\/\/www.tun.com\/home\/?p=18946"},"modified":"2025-02-26T16:15:42","modified_gmt":"2025-02-26T16:15:42","slug":"new-ai-tool-read-chest-x-rays-like-a-radiologist","status":"publish","type":"post","link":"https:\/\/www.tun.com\/home\/new-ai-tool-read-chest-x-rays-like-a-radiologist\/","title":{"rendered":"New AI Tool Read Chest X-Rays Like a Radiologist"},"content":{"rendered":"\n<div class=\"wp-block-group\"><div class=\"wp-block-group__inner-container is-layout-constrained wp-block-group-is-layout-constrained\">\n<div class=\"wp-block-uagb-blockquote uagb-block-e7eb3fc3 uagb-blockquote__skin-border uagb-blockquote__stack-img-none\"><blockquote class=\"uagb-blockquote\"><div class=\"uagb-blockquote__content\">Researchers at the University of Arkansas have created a pioneering AI tool, ItpCtrl-AI, that mimics a radiologist&#8217;s gaze to interpret chest X-rays. This innovative approach aims to increase trust, transparency and accuracy in AI diagnoses.<\/div><footer><div class=\"uagb-blockquote__author-wrap uagb-blockquote__author-at-left\"><\/div><\/footer><\/blockquote><\/div>\n\n\n\n<div class=\"wp-block-group is-content-justification-space-between is-nowrap is-layout-flex wp-container-core-group-is-layout-0dfbf163 wp-block-group-is-layout-flex\"><div style=\"font-size:16px;\" class=\"has-text-align-left wp-block-post-author\"><div class=\"wp-block-post-author__content\"><p class=\"wp-block-post-author__name\">The University Network<\/p><\/div><\/div>\n\n\n<div class=\"wp-block-uagb-social-share uagb-social-share__outer-wrap uagb-social-share__layout-horizontal uagb-block-ee584a31\">\n<div class=\"wp-block-uagb-social-share-child uagb-ss-repeater uagb-ss__wrapper uagb-block-ec619ce7\"><span class=\"uagb-ss__link\" data-href=\"https:\/\/www.facebook.com\/sharer.php?u=\" tabindex=\"0\" role=\"button\" aria-label=\"facebook\"><span class=\"uagb-ss__source-wrap\"><span class=\"uagb-ss__source-icon\"><svg xmlns=\"https:\/\/www.w3.org\/2000\/svg\" viewBox=\"0 0 512 512\"><path d=\"M504 256C504 119 393 8 256 8S8 119 8 256c0 123.8 90.69 226.4 209.3 245V327.7h-63V256h63v-54.64c0-62.15 37-96.48 93.67-96.48 27.14 0 55.52 4.84 55.52 4.84v61h-31.28c-30.8 0-40.41 19.12-40.41 38.73V256h68.78l-11 71.69h-57.78V501C413.3 482.4 504 379.8 504 256z\"><\/path><\/svg><\/span><\/span><\/span><\/div>\n\n\n\n<div class=\"wp-block-uagb-social-share-child uagb-ss-repeater uagb-ss__wrapper uagb-block-32d99934\"><span class=\"uagb-ss__link\" data-href=\"https:\/\/twitter.com\/share?url=\" tabindex=\"0\" role=\"button\" aria-label=\"twitter\"><span class=\"uagb-ss__source-wrap\"><span class=\"uagb-ss__source-icon\"><svg xmlns=\"https:\/\/www.w3.org\/2000\/svg\" viewBox=\"0 0 512 512\"><path d=\"M389.2 48h70.6L305.6 224.2 487 464H345L233.7 318.6 106.5 464H35.8L200.7 275.5 26.8 48H172.4L272.9 180.9 389.2 48zM364.4 421.8h39.1L151.1 88h-42L364.4 421.8z\"><\/path><\/svg><\/span><\/span><\/span><\/div>\n\n\n\n<div class=\"wp-block-uagb-social-share-child uagb-ss-repeater uagb-ss__wrapper uagb-block-1d136f14\"><span class=\"uagb-ss__link\" data-href=\"https:\/\/www.linkedin.com\/shareArticle?url=\" tabindex=\"0\" role=\"button\" aria-label=\"linkedin\"><span class=\"uagb-ss__source-wrap\"><span class=\"uagb-ss__source-icon\"><svg xmlns=\"https:\/\/www.w3.org\/2000\/svg\" viewBox=\"0 0 448 512\"><path d=\"M416 32H31.9C14.3 32 0 46.5 0 64.3v383.4C0 465.5 14.3 480 31.9 480H416c17.6 0 32-14.5 32-32.3V64.3c0-17.8-14.4-32.3-32-32.3zM135.4 416H69V202.2h66.5V416zm-33.2-243c-21.3 0-38.5-17.3-38.5-38.5S80.9 96 102.2 96c21.2 0 38.5 17.3 38.5 38.5 0 21.3-17.2 38.5-38.5 38.5zm282.1 243h-66.4V312c0-24.8-.5-56.7-34.5-56.7-34.6 0-39.9 27-39.9 54.9V416h-66.4V202.2h63.7v29.2h.9c8.9-16.8 30.6-34.5 62.9-34.5 67.2 0 79.7 44.3 79.7 101.9V416z\"><\/path><\/svg><\/span><\/span><\/span><\/div>\n<\/div>\n<\/div>\n<\/div><\/div>\n\n\n\n<p>Researchers at the University of Arkansas have unveiled a transformative AI tool capable of interpreting chest X-rays by mimicking the gaze patterns of radiologists, marking a significant milestone in medical diagnostics. <\/p>\n\n\n\n<p>Developed by Ngan Le, an assistant professor of computer science and computer engineering at U of A, and her team, the AI framework, called ItpCtrl-AI, uses a transparent and highly accurate method to diagnose conditions such as fluid in the lungs, an enlarged heart, or cancer.<\/p>\n\n\n\n<p>While AI can scan a chest X-ray and diagnose whether an abnormality is caused by fluid in the lungs, an enlarged heart or cancer, &#8220;being right is not enough,&#8221; Le said in a <a href=\"https:\/\/news.uark.edu\/articles\/75787\/new-ai-tool-mimics-radiologist-gaze-to-read-chest-x-rays\" target=\"_blank\" rel=\"noopener\" title=\"\">news release<\/a>. Instead, it is important to &#8220;understand how the computer makes its diagnosis.&#8221;<\/p>\n\n\n\n<p>The importance of transparency in AI decision-making cannot be overstated, particularly in medicine, where trust is paramount. Le emphasized the necessity of comprehending the AI&#8217;s thought process to foster trust among doctors and patients alike. <\/p>\n\n\n\n<p>&#8220;When people understand the reasoning process and limitations behind AI decisions, they are more likely to trust and embrace the technology,\u201d she added.<\/p>\n\n\n\n<p>ItpCtrl-AI stands out by recording where radiologists look and how long they focus on specific areas of chest X-rays. This data generates a heat map guiding the AI to identify abnormalities similarly to a radiologist. Unlike traditional &#8220;black box&#8221; AI systems, this method allows for adjustments and corrections to improve the accuracy of diagnoses.<\/p>\n\n\n\n<p><a href=\"https:\/\/www.sciencedirect.com\/science\/article\/abs\/pii\/S0933365724002963\" target=\"_blank\" rel=\"noopener\" title=\"\">Published<\/a> in the journal Artificial Intelligence in Medicine, the study&#8217;s outcomes suggest that transparent AI frameworks in medical diagnostics not only enhance accuracy but also bolster confidence in AI-generated results.<\/p>\n\n\n\n<p>&#8220;If an AI medical assistant system diagnoses a condition, doctors need to understand why it made that decision to ensure it is reliable and aligns with medical expertise,&#8221; Le added. <\/p>\n\n\n\n<p>This transparency makes ItpCtrl-AI an accountable tool in fields where the stakes are exceedingly high, such as medicine, autonomous driving and finance.<\/p>\n\n\n\n<p>The pioneering work also includes partnerships with the MD Anderson Cancer Center in Houston. The team is now progressing towards refining ItpCtrl-AI to interpret more complex, three-dimensional CT scans. <\/p>\n\n\n\n<p>The development of ItpCtrl-AI represents a significant leap in AI technology, making AI systems more interpretable and trustworthy while keeping them aligned with human values and ethical standards. As AI continues to evolve, innovations like ItpCtrl-AI will be crucial in ensuring that these systems remain beneficial and reliable partners in various high-stakes fields.\u00a0<\/p>\n","protected":false},"excerpt":{"rendered":"<p>Researchers at the University of Arkansas have unveiled a transformative AI tool capable of interpreting chest X-rays by mimicking the gaze patterns of radiologists, marking a significant milestone in medical diagnostics. Developed by Ngan Le, an assistant professor of computer science and computer engineering at U of A, and her team, the AI framework, called [&hellip;]<\/p>\n","protected":false},"author":3,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"single-no-separators","format":"standard","meta":{"_acf_changed":false,"_uag_custom_page_level_css":"","_monsterinsights_skip_tracking":false,"_monsterinsights_sitenote_active":false,"_monsterinsights_sitenote_note":"","_monsterinsights_sitenote_category":0,"footnotes":""},"categories":[8],"tags":[44],"class_list":["post-18946","post","type-post","status-publish","format-standard","hentry","category-ai","tag-university-of-arkansas"],"acf":[],"aioseo_notices":[],"uagb_featured_image_src":{"full":false,"thumbnail":false,"medium":false,"medium_large":false,"large":false,"1536x1536":false,"2048x2048":false},"uagb_author_info":{"display_name":"The University Network","author_link":"https:\/\/www.tun.com\/home\/author\/funky_junkie\/"},"uagb_comment_info":0,"uagb_excerpt":"Researchers at the University of Arkansas have unveiled a transformative AI tool capable of interpreting chest X-rays by mimicking the gaze patterns of radiologists, marking a significant milestone in medical diagnostics. Developed by Ngan Le, an assistant professor of computer science and computer engineering at U of A, and her team, the AI framework, called&hellip;","_links":{"self":[{"href":"https:\/\/www.tun.com\/home\/wp-json\/wp\/v2\/posts\/18946","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.tun.com\/home\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.tun.com\/home\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.tun.com\/home\/wp-json\/wp\/v2\/users\/3"}],"replies":[{"embeddable":true,"href":"https:\/\/www.tun.com\/home\/wp-json\/wp\/v2\/comments?post=18946"}],"version-history":[{"count":6,"href":"https:\/\/www.tun.com\/home\/wp-json\/wp\/v2\/posts\/18946\/revisions"}],"predecessor-version":[{"id":18966,"href":"https:\/\/www.tun.com\/home\/wp-json\/wp\/v2\/posts\/18946\/revisions\/18966"}],"wp:attachment":[{"href":"https:\/\/www.tun.com\/home\/wp-json\/wp\/v2\/media?parent=18946"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.tun.com\/home\/wp-json\/wp\/v2\/categories?post=18946"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.tun.com\/home\/wp-json\/wp\/v2\/tags?post=18946"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}